DEVELOPMENT... OpenML
Run
64029

Run 64029

Task 3810 (Supervised Classification) arsenic-male-bladder Uploaded 17-11-2014 by Felicia West
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Flow

weka.MultiBoostAB_SPegasos(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.SPegasos(2)_E500
weka.SPegasos(2)_F0
weka.SPegasos(2)_L1.0E-4
weka.MultiBoostAB_SPegasos(2)_C3
weka.MultiBoostAB_SPegasos(2)_P100
weka.MultiBoostAB_SPegasos(2)_S1
weka.MultiBoostAB_SPegasos(2)_I80
weka.MultiBoostAB_SPegasos(2)_Wweka.classifiers.functions.SPegasos

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

21 Evaluation measures

Area under ROC curve
0.8147
Per class
Build CPU time
3.7543
Build memory
579462637.4669
F measure
0.9742
Per class
Kappa
0.6553
KB relative information score
68.7396
Mean absolute error
0.0351
Mean prior absolute error
0.0837
Number of instances
559
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9749
Per class
Predictive accuracy
0.9767
Prior entropy
0.2628
Recall
0.9767
Per class
Relative absolute error
0.4198
Root mean prior squared error
0.2027
Root mean squared error
0.1568
Root relative squared error
0.7734
SciMark benchmark
939.9473